New Redundant Manipulator Robot with Six Degrees of Freedom Controlled with Visual Feedback

The design and implementation stages of a redundant robotized manipulator with six Degrees Of Freedom (DOF), controlled with visual feedback by means of computational software, is presented. The various disciplines involved in the design and implementation of the manipulator robot are highlighted in their electric as well as mechanical aspects. Then, the kinematics equations that govern the position and orientation of each link of the manipulator robot are determined. The programming of an artificial vision system and of an interface that control the manipulator robot is designed and implemented. Likewise, the type of position control applied to each joint is explained, making a distinction according to the assigned task. Finally, functional mechanical and electric tests to validate the correct operation of each of the systems of the manipulator robot and the whole robotized system are carried out.

Multi-View RGB-D Synchronized Video Acquisition and Temporally Coherent 3D Animation Reconstruction Using Multiple Kinects

This chapter introduces a system for acquiring synchronized multi-view color and depth (RGB-D) video data using multiple off-the-shelf Microsoft Kinect and methods for reconstructing temporally coherent 3D animation from the multi-view RGB-D video data. The acquisition system is very cost-effective and provides a complete software-based synchronization of the camera system. It is shown that the data acquired by this framework can be registered in a global coordinate system and then can be used to reconstruct the 360-degree 3D animation of a dynamic scene. In addition, a number of algorithms to reconstruct a temporally-coherent representation of a 3D animation without using any template model or a-prior assumption about the underlying surface are also presented. It is shown that despite some limitations imposed by the hardware for the synchronous acquisition of the data, a reasonably accurate reconstruction of the animated 3D geometry can be obtained that can be used in a number of applications.

A Nearest Opposite Contour Pixel Based Thinning Strategy for Character Images

Thinning of character images is a big challenge. Removal of strokes or deformities in thinning is a difficult problem. In this paper, we have proposed a nearest opposite contour pixel based thinning strategy used for performing skeletonization of printed and handwritten character images. In this method, we have used shape characteristics of text to get skeleton of nearly same as the true character shape. This approach helps to preserve the local features and true shape of the character images. The proposed algorithm produces one pixel-width thin skeleton. As a by-product of our thinning approach, the skeleton also gets segmented into strokes in vector form. Hence further stroke segmentation is not required. Experiment is done on printed English and Bengali characters and we obtain less spurious branches comparing with other thinning methods without any post-processing.

A Study on Different Edge Detection Techniques in Digital Image Processing

Image segmentation is one of the fundamental problems in image processing. In digital image processing, there are many image segmentation techniques. One of the most important techniques is Edge detection techniques for natural image segmentation. Edge is a one of the basic feature of an image. Edge detection can be used as a fundamental tool for image segmentation. Edge detection methods transform original images into edge images benefits from the changes of grey tones in the image. The image edges include a good number of rich information that is very significant for obtaining the image characteristic by object recognition and analyzing the image. In a gray scale image, the edge is a local feature that, within a neighborhood, separates two regions, in each of which the gray level is more or less uniform with different values on the two sides of the edge. In this paper, the main objective is to study the theory of edge detection for image segmentation using various computing approaches.

A Study on Various Image Processing Techniques and Hardware Implementation Using Xilinx System Generator

This article reviews the various image processing techniques in MATLAB and also hardware implementation in FPGA using Xilinx system generator. Image processing can be termed as processing of images using mathematical operations by using various forms of signal processing techniques. The main aim of image processing is to extract important features from an image data and process it in a desired manner and to visually enhance or to statistically evaluate the desired aspect of the image. This article provides an insight into the various approaches of Digital Image processing techniques in Matlab. This article also provides an introduction to FPGA and also a step by step tutorial in handling Xilinx System Generator. The Xilinx System Generator tool is a new application in image processing and offers a friendly environment design for the processing. This tool support software simulation, but the most important is that can synthesize in FPGAs hardware, with the parallelism, robust and speed, this features are essentials in image processing. Implementation of these algorithms on a FPGA is having advantage of using large memory and embedded multipliers. Advances in FPGA technology with the development of sophisticated and efficient tools for modelling, simulation and synthesis have made FPGA a highly useful platform.

Educational Data Mining and Indian Technical Education System

Educational Data Mining (EDM) is emerged as a powerful tool in past decade and is concerned with developing methods to explore the unique types of data in educational settings. Using these methods, to better understand students and the settings in which they learn. Different unknown patterns using classification, Clustering, Association rule mining, decision trees can be discovered from this educational data which could further be beneficial to improve teaching and learning systems, to improve curriculum, to support students in the form of individual counseling, improving learning outcomes in terms of students' satisfaction and good placements as well. Therefore a literature survey has been carried out to explore the most recent and relevant studies in the field of data mining in Higher and Technical Education that can probably portray a pathway towards the improvement of the quality education in technical institutions.

Feature Detectors and Descriptors Generations with Numerous Images and Video Applications

Feature detectors have a critical role in numerous applications such as camera calibrations, object recognition, biometrics, medical applications and image/video retrieval. One of its main tasks is to extract point correspondences “Interest points” between two similar scenes, objects, images or video shots. Extensive research has been done concerning the progress of visual feature detectors and descriptors to be robust against image deformations and achieve reduced computational speed in real-time applications. The current chapter introduced an overview of feature detectors such as Moravec, Hessian, Harris and FAST (Features from Accelerated Segment Test). It addressed the feature detectors' generation over time, the principle concept of each type, and their use in image/video applications. Furthermore, some recent feature detectors are addressed. A comparison based on these points is performed to illustrate their respective strengths and weaknesses to be a base for selecting an appropriate detector according to the application under concern.

Medical Video Processing

In today's medical environments, imaging technology is extremely significant to provide information for accurate diagnosis. An increasing amount of graphical information from high resolution 3D scanners is being used for diagnoses. Improved medical data quality become one of the major aims of researchers. This leads to the development of various medical modalities supported by cameras that can provide videos for the human body internal for surgical purposes and more information for accurate diagnosis. The current chapter studied concept of the video processing, and its application in the medical domain. Based on the highlighted literatures, it is convinced that video processing and real time frame will have outstanding value in the clinical environments.

Insilico Approach for Epitope Prediction toward Novel Vaccine Delivery System Design

Vaccines build a defense mechanism against the disease causing agents through the immune system stimulation and disease agents' imitation. Some of the vaccines contain a part of the disease causing agents that are either weakened or dead. Along with using vaccines with viral infections, it can be used against the various types of cancers for both therapy and prevention. The use of cancer's vaccines in cancer therapies is called immunotherapy. It can be done either by specific cancer vaccine or universal cancer vaccine that contains tumor antigens, which stimulate the immune system. This in turn initiates various mechanisms that terminate tumor cells and prevents recurrence of these tumors. The present work proposed an Insilico approach in epitope prediction and analysis of antigenecity and Immunogenecity of Haemophilus influenzae strains. It was interested with the design of a novel vaccine delivery system with better adjuvancity, where vaccine adjuvant is significant for the improvement of the antigens' immunogenicity that present in the vaccines. The conducted insilico approaches selected the best strain target proteins, m strain selection, epitope prediction, antigenicity and immunogenicity prediction of target proteins to find out the best targets.

On the Use of Motion Vectors for 2D and 3D Error Concealment in H.264/AVC Video

The fundamental principles of the coding/decoding H.264/AVC standard are introduced emphasizing the role of motion estimation and motion compensation (MC) in error concealment using intra- and inter-frame motion estimates, along with other features such as the integer transform, quantization options, entropy coding possibilities, deblocking filter, among other provisions. Efficient MC is one of the certain reasons for H.264/AVC superior performance compared to its antecedents. The H.264/AVC has selective intra-prediction and optimized inter-prediction methods to reduce temporal and spatial redundancy more efficiently. Motion compensation/prediction using variable block sizes and directional intra-prediction to choose the adequate modes help decide the best coding. Unfortunately, motion treatment is a computationally-demanding component of a video codec. The H.264/AVC standard has solved problems its predecessors faced when it comes to image quality and coding efficiency, but many of its advantages require an increase in computing complexity.